The Latest in AI: Job Loss, Elon & Sam Altman Chip Race & the "AI Bubble" w/ Brian Elliott (Blitzy), Emad Mostaque & Dave Blundin | EP #197

Summary

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Moonshots with Peter Diamandis

EP #197: The Latest in AI — Job Loss, Elon & Sam Altman Chip Race & the "AI Bubble"

Guests: Brian Elliott (Blitzy), Emad Mostaque (Intelligent Internet), Dave Blundin (Link Exponential Ventures)
Date: September 26, 2025

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Overview

In this episode, Peter Diamandis and co-hosts explore the relentless acceleration of artificial intelligence, its wide-reaching impact on jobs and education, and the trillion-dollar race for AI compute infrastructure. Special guests Brian Elliott, Emad Mostaque, and Dave Blundin offer insider commentary on the "AI wars" (Google, Microsoft, OpenAI, Meta, xAI), the transforming landscape of higher education, the ongoing data center arms race, the coming disruption in healthcare and capital markets, and the underlying question: is this an AI bubble — or a true economic inflection point?

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Key Discussion Points & Insights

1. Is AI a Bubble?

• Consensus: Absolutely not. The panel draws contrasts to the dotcom era, arguing that AI produces real, rapidly growing economic value.
• Dave Blundin: "Nothing's going to change the world more than what's going on right now. It is definitely not a bubble. It's not even vaguely like a bubble." (00:06)
• Imad Mostaque: "AI is useful. People pay for it because it has economic value." (00:00)
• Data Evidence: Nvidia's meteoric rise matches up with earnings growth, not just speculation. CapEx transforms immediately into increased output via AI applications. (74:58–79:21)

2. The Higher Education Crisis

• Context: Value perception of college has plummeted. In 2010, 75% of Americans said college was "very important". In 2025, only 35% agree; meanwhile, "not too important" responses have soared.
• Peter Diamandis: "The cost of tuition goes through the roof. The perceived value of the education has been plummeting ... you're saddled with debt and you don't make it back because you're not getting the jobs. It's crazy." (03:08)
• Brian Elliott: Credentials matter more than content/learning; dropping out of an elite school can sometimes get you funded faster than graduating.
• Imad Mostaque: The "AI drop" is accelerating, with early-stage graduates struggling to find employment — and AI amplifying this trend. (04:41–05:26)
• Systemic forces: Top universities are shielded by massive endowments; second- and third-tier schools face existential risk.
• Future vision: "We haven't seen the first AI university yet, which I think is going to be really interesting..." (09:24)

3. AI Agents and Job Displacement

• Impact: Rapid automation threatens knowledge and skilled labor. The only "future-proof" path may be entrepreneurship or domain-specific innovation using AI.
• Peter Diamandis: "The only career of the future that really matters... is being an entrepreneur. It's not marching up the career path." (05:26)
• Dave Blundin: Immediate productivity gains can lead to staff reduction, especially in fast-growing companies (e.g., Duolingo, Salesforce). But many CEOs and public figures are now dampening their messaging to avoid panic. (86:45)
• Imad Mostaque: "Humans will have negative value in cognitive labor in a few years ... if you're in a job where your role is to beat other people, as in private sector competitive jobs, you're not going to beat an AI." (83:00)
• Real-world stats: GPT4 outperforms physicians at diagnosis 92% vs. 74% for humans; adding a human lowers performance. (84:15)

4. The Compute Arms Race: Chips, Data Centers, and Power

• Stakes: Google, OpenAI, xAI, Meta, and others are racing to secure rare compute, build immense data centers, and secure energy—described as unprecedented capital war.
• Highlights:
  • xAI (Elon Musk) pledges to hit 10 gigawatts of compute, then 100GW, then 1 terawatt: "It's basically like as much as a state." (19:26)
  • OpenAI, via Nvidia partnership, throwing $100 billion at compute, planning multi-square-mile "superbrain" campuses. (20:00–21:26)
  • Scarcity: Annual chip production is far less than anticipated demand; even dominant players must maneuver, hedge, and optimize to maintain access.
  • Compute is power: "We're converting electrons into intelligence and into crypto." (22:24)
• Key quote: Greg Brockman: "By 2030, we will be in a world of material abundance... except for compute, which will be absolutely scarce." (27:13–27:31)

5. AI Model Wars: Who Wins?

• Gemini (Google) overtaking ChatGPT in US iOS installs, thanks to Google's distribution muscle. (12:29–12:51)
• Alibaba’s Qwen model rising due to relentless iteration and massive data.
• Grok5 (xAI) leads AGI benchmarks, e.g., ARC AGI v2, New York Times Connections—though there's suspicion of "benchmaxing" by training specifically to optimize for each test. (14:38–18:38)
• Brian Elliott: Cost per task matters as much as model intelligence: scalable, cheap compute will determine the winner. (16:05)

6. Vertical Integration: Hardware, Models, Applications

• Google: Vertically integrated with TPUs, no Nvidia tax, five times more power efficient for certain AI tasks.
• Meta (Zuckerberg): Committed $600 billion to US data centers by 2028: "Better to lose billions than be late to superintelligence." (35:22)
• Microsoft & OpenAI: In a high-stake dance/trade for compute and ownership control, with OpenAI aiming to restructure into a for-profit and spawn a record-breaking nonprofit endowment. (32:12–34:49)

7. Economic Transformation & Tokenized Securities

• Tokenized securities, 24/7 trading: NASDAQ and Robinhood leading the charge to on-chain finance—stocks, and even privates like OpenAI and SpaceX, soon to be tokenized and tradeable. (88:05–93:16)
• Dave Blundin: Blockchains and AI can replace outdated public market regulations, reporting, and liquidity demands, enabling smaller, faster IPO-like structures.

8. Healthcare and Drug Discovery Revolution

• Wearables: Apple Watch receives FDA clearance for hypertension detection; CGM, Oura, "insideables" feed actionable personal health data to AI.
• AI-accelerated drug discovery:
  • First AI-designed drugs hit clinical trials; process cut from years to months.
  • 150+ new small molecule drugs discovered by AI in 2025; phase 1 success rates 80–90%, far above historical averages. (96:46–97:56)
  • Emad Mostaque predicts the FDA will soon demand in silico (AI-predicted) trial results.

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Notable Quotes & Memorable Moments

• On AI Bubble vs. Reality:
  "AI is useful. People pay for it because it has economic value." – Imad Mostaque (00:00)

• On Higher Education’s Obsolescence:
  "We can build a nuclear reactor on campus faster than we will ever change this curriculum." – Dave Blundin (03:03)

• On Compute Scarcity as Bottleneck:
  "Abundance everywhere except compute scarcity... fundamentally, it is a physical infrastructure problem, not just a software problem." – Greg Brockman (27:13–27:31)

• On Opportunity:
  "There will never be a better time. There never has been a better time. Maybe tomorrow." – Dave Blundin (98:57)

• On Human Value in Work:
  "Humans will have negative value in cognitive labor in a few years... If you’re in a job where your role is to beat other people... you’re not going to beat an AI." – Imad Mostaque (83:00)

• On The Infrastructure Armistice:
  "We’re converting electrons into intelligence and into, into crypto." – Peter Diamandis (22:24)

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Timestamps for Key Segments

• Intro & Main Theme

  • Is AI a Bubble? (00:00–00:25)

• Education Crisis & AI

  • College Value Plummets (01:21–10:20)
  • The AI University Paradigm (09:24–10:20)

• AI Wars and Compute Race

  • Gemini, ChatGPT, Alibaba Qwen, Grok5* (12:29–19:00)
  • xAI, OpenAI, Meta Data Center Race (19:00–23:24)
  • Physical limits of chip production, scarcity (21:26–25:50)

• AI’s Impact on the Labor Market

  • Unemployment and automation (05:26–08:23, 81:39–86:45)
  • Three-day workweek? The end of human cognitive labor (81:39–85:22)
  • Domain Experts and New Entrepreneurship (47:14–53:58)

• Hardware & Integration

  • Google, TPUs, Vertically Integrated AI (44:39–46:11)

• Structural Changes: Economy & Finance

  • Tokenized Securities, Blockchain IPOs (88:05–93:36)
  • Abundance, Immediate Payback vs. Bubble (74:22–79:21)

• Health & Drug Discovery

  • Wearable’s FDA Cleared for Hypertension (93:36–96:46)
  • AI-accelerated Drug Discovery (96:46–98:18)

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Final Takeaways

• Relentless Acceleration: AI progress, economic impact, and infrastructure buildout are all compounding more quickly than any previous tech transformation — and show every sign of continuing exponential growth.
• Labor Market Disruption: Entrepreneurs and domain experts who leverage AI are best positioned, while traditional credentialing and middle-skilled knowledge work are increasingly at risk.
• AI Will Touch Everything: From university reform to tokenized capital markets, from autonomous “wearables” for health to robots in homes and factories, the platforms being built now are laying the groundwork for a vastly different society.
• Now is the Window: As Dave Blundin and Brian Elliott both stress, there may never be a better time for bold action, experimentation, learning, and investing in this technological wave.

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For Further Exploration

• Slides & Resources: diamandis.com/wtf
• Newsletter (Metatrends): dashmandis.com/metatrends
• Intelligent Internet Book: thelasteconomy.com

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*For a full, detailed transcript and more resources, visit the podcast website or subscribe to Peter Diamandis' newsletter.

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Transcript

[Imad Mustaq]

AI is useful. People pay for it because it has economic value.

[Peter Diamandis]

AI is not a bubble.

[Dave Blunden]

Nothing's going to change the world more than what's going on right now. It is definitely not a bubble. It's not even vaguely like a bubble.

[Imad Mustaq]

AI until a few months ago, it was like having a very smart goldfish memory buddy next to you that you had to oversee all the time. Now it's the set it and forget it. And it can use millions of tokens, millions of lines of code.

[Peter Diamandis]

Gemini overtakes ChatGPT in the US so this is based on iOS sales Graphics 5 could reach AGI first.

[Imad Mustaq]

It's going to be a crazy couple of years now with this and there's just not enough energy, compute infrastructure, anything.

[Peter Diamandis]

As a CEO and entrepreneur, do you worry about getting access to the compute you need?

[Brian Elliott]

You really want to be a player where everybody else wins?

[Peter Diamandis]

When you win, there will be some kind of a breakthrough on compute. Is it going to be from Quantum? Is it going to be from now.

[Dave Blunden]

That'S a moonshot, ladies and gentlemen.

[Peter Diamandis]

Everybody, welcome to Moonshots. Another episode of WTF just happened in tech. I'm here with my moonshot mates. Dave Blunden, the CEO and head of Link Exponential Ventures. Imad Mustaq, the head of Intelligent Internet. My dear friend Imad, you're in where? Today you're in London.

[Imad Mustaq]

Yep, in London.

[Peter Diamandis]

Nice. And Brian Elliott, who you guys met on a previous podcast. Brian is the CEO of Blitzi. So a lot to discuss as always. If you are ready to plug in. Guys, start taking notes, start listening. This is the world that is transforming how we live our lives. Before we begin with anything else, I want to talk about the wake up call for colleges and universities. It's pretty extraordinary. So this is a chart that's just out about how Americans perceive the value of college. And if you take a look at this graphic and I'll sort of look at it for everybody here, people who say it's very important have dropped from 75% in 2010 to 35%. Right the wrong direction. If you're a college or university, not too important on the other end has gone from 5% up to 24%. So for me, you know, universities have a problem. Dave, we've been talking about this for a while.

[Dave Blunden]

Yeah.

[Peter Diamandis]

Yeah. Your thoughts?

[Dave Blunden]

I couldn't believe, like, I knew this was happening, but these numbers blew my mind. I immediately sent it off to David Siegel, you know, the founder of two Sigma.

[Peter Diamandis]

Yeah.

[Dave Blunden]

Because we're going to go meet with Sally Kornbluth. The president of MIT in a few weeks. Like, holy crap. This is a really, really big deal. And you know, Peter, you've been saying it for a long time. The cost of tuition goes through the roof. The perceived value of the education has been plummeting. Not because it's worth less in any fundamental way, but what you can learn has grown so quickly and it hasn't made it into the curriculum. And remember, Peter, we had that meeting with the head of. I don't want to name names, one of the top guys at mit.

[Peter Diamandis]

Yeah, I remember it.

[Dave Blunden]

We can build a nuclear reactor on campus faster than we will ever change this curriculum. Oh my God. It's like.

[Peter Diamandis]

You know the problem with if you're an accredited university is you're not iterating your curriculum fast enough and it just becomes irrelevant before you graduate. So tuition is up 180% since 2005. Room and board in a private university today is a quarter of a million dollars. And you're saddled with debt and you don't make it back because you're not getting the jobs. It's crazy. Brian, you're closer to college than I am right now. How do you think about this?

[Dave Blunden]

I mean, it's.

[Brian Elliott]

College has been a credentialing program for a long time. Right. And so it was the act of getting into MIT that was actually impressive. It was less to do with what MIT could specifically teach you because their curriculum is taught all over the world. And so for free, by the way, dropouts of mit. Yeah, totally for free.

[Peter Diamandis]

Yeah.

[Brian Elliott]

Dropouts get funded incredibly fast. And so what's the point of staying for that extra few years? Right? And so there's this unbundling right now that's happening between the credentialing that you can get just from getting in or from going to Y Combinator or from having a portfolio site that's really good. There's other ways to get credentialed that just weren't possible before. And that's kind of compounded with this big curriculum. Like, I'd love to see the problem of.

[Peter Diamandis]

I'd love to see the graph of dropout rate in year one, two, three, sort of increasing over time, especially in the last few years. And imod, I mean, you know, you sort of stopped and started and, you know, finally went and collected the piece of paper. Tell me about how you think about this.

[Imad Mustaq]

Yeah, it took me like 20 years to get my pieces of paper from Oxford. That was a hole to do. I think that there were probably two things here. I think the first boom was that tuition expense boom that we saw. I think that's caught in the first part. I think the second part was probably Covid. Like that was a terrible experience for a lot of people in college. And also I think it showed things up. And now we're heading towards the AI drop that we, as it were, whereby we saw that paper by Eric Lofsensen and others that showed early stage graduates starting to lose the ability to get jobs. So that's just going to go. So again, it falls into question, what is that? And that's before we even get into the foreign students and what's going to happen there with the visa changes, etc.

[Peter Diamandis]

And this is the second blow. This is the kill shot here. This is a graph that, you know, titled college educated are unemployed longer. So it used to be that you'd go to college to get your job. And we've talked about this on this pod a number of times. The only career of the future that really matters, in my opinion, I think in all of our opinion, is being an entrepreneur. It's not marching up the career path. And so this is a graph between 2000 and 2025. And what we see in terms of unemployment is the college graduates increasing unemployment while everybody else with some college or just high school. In fact, high school college graduates are becoming more employed. If they didn't go to college, they go to trade school.

[Dave Blunden]

Well, yeah, I love that one pixel there just last summer where the most unemployable people in the world are college graduates. It's just hilarious. But if you look bad PR for colleges, bad priority. Well, if you look back 2000, that's what I'm used to hearing, which is, hey, if you go to college and you graduate, you're over twice as likely to get a great job. And that's exactly what you see in the data just 20, 25 years ago. So this is a pretty rapid shift in society's perception of the value of a degree. Now keep in mind, within this entire chart, the unemployment rate is extremely low. It's like four and a half percent. So most people are finding jobs. It's not implying that you. Well, actually we can go, we can go down that path. Actually, it's very hard for this year's graduating class to find jobs. It's shockingly hard.

[Brian Elliott]

What does this look like if we stratosphere like the top 10 versus everybody else? Because I think there's been a sort of a blowing up of people getting college degrees at, I would say sub tier institutions because it's incredibly profitable for these institutions. Even though they maintain a nonprofit status, they're growing the size of their employee base and their student base as a sort of a way to just fund fun poor education.

[Peter Diamandis]

In a way, I do agree with what you said earlier, Brian, which is what really matters out of a college education is the fact that you got accepted by a specific university. When someone says, so Imad, you went to Oxford or Peter or Dave or Brian, you went to mit, they don't ask did you graduate? They don't ask what was your gpa. They don't ask you about what you studied. It was like yeah, I went to mit. That's all that matters. That's the highest order bit and it's crazy. So there should be a brand new program that MIT offers where it accepts you but doesn't expect you to go.

[Dave Blunden]

Yeah. If you go to the next slide. It really makes Brian's point, okay, here's your tuition getting completely out of control. But that top 10 top 15 schools are hugely endowment driven. In fact these the endowment returns contributing to the budget are over twice as much as all tuition combined. So those, I want to read this.

[Peter Diamandis]

For those who are listening. It says college tuition versus other expenses. Cumulative percentage price change since 1983, which is when I was at MIT. So it's up almost 900% in tuition over that time. 5.6 increase. Average annual increase.

[Dave Blunden]

Yes. You got a handful of schools that don't even care about the tuition. They'll be fine because their endowments are so big. And then you got this really slippery slope of schools that need the tuition desperately to stay open at a time when people are not really perceiving the value of the degree. So that's where it gets really ugly. Right around school number 40 to 400.

[Peter Diamandis]

If I'm the board member at MIT Harvard, I'm probably not as worried, but if I'm at a second tier school, I'm like, holy shit, what do we do? We need to reinvent how we educate. Iman, you and I have talked about the value of education and the fact that the best educator in the world will be AI. What's your thought here?

[Imad Mustaq]

Yeah, I think there's the credentialing part, but university became something that you just passed by default versus programs like Gauntlet and others where you actually have to work really hard to succeed and get through with high dropout rates. I think the world we're going to now is one very competitive one where the people that use AI, there's nothing you can't master with AI now faster. We've seen Alpha School and others Show Just in two hours a day of tuition, they're typing 0.5% in the world, even with academic papers. I think it's going to be similar and I think there'll be a huge amount of arbitrage because it just got too expensive. Like in the UK, Oxford cost $13,000 a year for tuition or like $60,000 a year if you're foreign. I think that people will go to the networks and they'll go to the places that embrace the technology to actually do what universities are meant to do, which is networks, knowledge, learn and more. But we haven't seen the first AI university yet, which I think is going.

[Peter Diamandis]

To be really interesting and really important. We're going to have McKinsey Price the CEO and Joe the co founder who's funded it on a podcast coming up. So those of you who are moms, dads, educators, you're going to get ready for a fun episode on how to reinvent secondary education in high school.

[Imad Mustaq]

All right. Actually, just I think one final thing.

[Peter Diamandis]

Yeah, please.

[Imad Mustaq]

Maybe the endowment should be putting big supercompute clusters down because the universities in the US don't have them. That'll probably be the biggest determinant of research quality in universities. How many GPEs you have?

[Dave Blunden]

I totally agree.

[Peter Diamandis]

I love that.

[Dave Blunden]

I think it's a no brainer.

[Peter Diamandis]

All right, mit, listen up here. You put the endowment to use.

[Dave Blunden]

They want to. There are forces in the school that desperately want to do exactly what Imad just said. I don't know what the friction is, but we'll work on it.

[Imad Mustaq]

Get JP Morgan to debt, fund it.

[Peter Diamandis]

Every week, my team and I study the top 10 technology metatrends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics, AGI and quantum computing to transport energy, longevity and more. There's no fluff, only the most important stuff that matters that impacts our lives, our companies and our careers. If you want me to share these metatrends with you, I write a newsletter twice a week, sending it out as a short 2 minute read via email. And if you want to discover the most important meta trends ten years before anyone else, this report's for you. Readers include founders and CEOs from the world's most disruptive companies and entrepreneurs building the world's most disruptive tech. It's not for you. If you don't want to be informed about what's coming, why it matters, and how you can benefit from it to subscribe for free, go to dashmandis.com metatrends to gain access to the trends ten years before anyone else. All right, now back to this episode. All right, let's jump into the AI wars, our favorite subject. Every week we're going to kick it off with the fact that Gemini overtakes ChatGPT in the US. So this is based on iOS sales, 150 million users. We've seen Gemini go through this viral element. I mean, love nanobanana, VO3 and others. And they've jumped into number one position. Any particular thoughts here?

[Dave Blunden]

I did not believe it because ChatGPT had such a huge lead. So I checked the App Store data directly and it is absolutely true. Now this is us. So chatgpt is still miles ahead globally, but Google can use its massive distribution power to push that. That's how Chrome bypassed Firefox. And you just push it out.

[Peter Diamandis]

Didn't bypass it. Blew it away.

[Dave Blunden]

Blew it away.

[Peter Diamandis]

Actually, I checked polymarkets on this. Interesting enough. So I checked on polymarket Score, which is really fun to do if you guys, if our subscribers haven't done that, look at it. So I first asked, when is Gemini 3 coming out? We've been waiting, waiting for Gemini 3 to do an episode on Gemini 3. The current top prediction is 40% by October 31st. So maybe by the end of next month. But here's the other prediction. Which AI model will be in first place? The best by the end of September, 99%. It was Google. But what was fascinating was the second best AI model by the end of September, 91% for Alibaba, for Quinn. I find that amazing. How do you think about that, Iman?

[Imad Mustaq]

Well, I think we've seen the gap close dramatically between those models. Kwen is releasing almost daily now. Today they had six model releases.

[Peter Diamandis]

Wow.

[Imad Mustaq]

And they're just accelerating. And I think that it would be difficult for them to have the best model, but they just have such reach with the billions of users that Alibaba has, the amount of data they have. And they've just got a really kick ass team there. And distribution matters so much. Like, I don't know anyone that uses threads. And number three there, right? It has 400 million monthly active users and 115 daily activity. 15 million daily active users. And I feel that this Gemini ChatGPT thing is the same thing, which is why people can be doubling down on the distribution. And now that we've got the reinforcement learning really coming through with the models, that's actually how they'll get really good. And I think that's going to be a real differentiator as we go forward. And again, we'll probably see the Qin models keeping up because they're used so widely now everywhere, and they are closing that gap.

[Peter Diamandis]

All right, not to be left out of the conversation, Grok5. This is a chart that Grok5 could reach AGI first. And the fact that we've seen it beating all the AGI benchmarks, and in particular here, what we have is Grok 5 reaching top marks on the Arc AGI benchmark, which is the abstract and reasoning corpus. So right now in the Arc AGI V2, Grok 4 has hit 15.9%, which is the highest known. Are you tracking these iman?

[Imad Mustaq]

Yeah, I mean, I think that we're continuing to see scales coming through here and this is going to be the first big mega run that we'll know about again. OpenAI might release their verifier runs, but all these benchmarks are saturating so fast. I think that. Who was it? Epoch Research predicted that every benchmark in the market today will be saturated within three years, four years.

[Peter Diamandis]

We need new benchmarkstrapolation, Dave.

[Imad Mustaq]

We need new benchmarks.

[Peter Diamandis]

But the crazy thing, crazy thing is.

[Dave Blunden]

What this is v2, though we already saturated v1, but v2 is crazy hard. Like, if this one saturates, then you're beyond superhuman intelligence. So if this one saturates in three years, we're in another universe, which it probably will.

[Brian Elliott]

I think more important is the cost per task on the X axis. It's very, very clear that if you're willing to throw more dollars at this, you're able to increase performance. And I think that's. I could care less on the last slide of, like, who the consumer user is. It's like when we throw more dollars at which models do we increase the quality of performance? And that's going to be who ends up winning.

[Imad Mustaq]

It's still only been one year since 01 was announced.

[Peter Diamandis]

That's crazy ancient history. That's funny. And so here we go. GROK for Fast Reasoning. I love these names, right? Just appending the end of them. Grok for Fast Reasoning ranks number one on the extended New York Times connection benchmark. So what is that? So this is based on New York Times puzzles, where players must group 16 words into four groups, each belonging to a common semantic category. The extended version, the original version, 436 puzzles, the extended version has 759 versions. I mean, these are just, you know, are these Vanities vanity benchmarks to sort of brag, get bragging rights.

[Dave Blunden]

Yeah, actually, I talked to Alex about this one. He's off in Europe today. But yes, by the way, I should.

[Peter Diamandis]

Say Salim is mia. Salim, where'd you go, buddy? And Alex is on a top secret mission in Europe. I'll leave it at that.

[Dave Blunden]

This is a really fun benchmark here though, because if you go to New York Times and you do the connections tests, it's a daily puzzle. It's really fun actually. My wife does it every single day with her friends. They made it harder by adding more categories to it. Four more categories. And you have to get it right the first time. When you do it on the New York Times website, it gives you three wrong answers before it says no, you're wrong. But the AI has to get it right the first time. But it really is a good test of general intelligence. Shockingly good. But the theory here is that the big foundation model companies are going to benchmax it. So they'll train on a bunch of data specific to this puzzle type to try to max it out. And you saw when Brian did the blitzi announcement on our podcast, very careful to say we topped Sweebench, but we did not tune or benchmax to that test. It just happens this way. And here we're almost sure that they're trying to get the PR by benchmaxing and optimizing toward the problem, but you can't prove it. But it isn't a crazy high score though to get in the 90 percents on this.

[Peter Diamandis]

Amazing. All right, here we go. This is going to be the data Center Wars Xai's Colossus 2, a gigawatt scale data center. 110,000 HP, 200 GPU clusters. I love this. 119 Air cooled chillers and Tesla megapacks. So this is the beginning of Colossus 2. Imad, you're tracking this, I'm sure.

[Imad Mustaq]

Yeah, I think Elon said he's going to be the first to a gigawatt. The first to 10 gigawatts in the first 2 terawatts.

[Peter Diamandis]

Yeah, this is his. His tweet from today. OpenAI is bragging about their Nvidia partnership. And here he is saying just as we were first to bring a gigawatt of coherent training compute online, we'll be the first to 10 gigawatts, 100 gigawatts and 1 terawatt. Love that.

[Imad Mustaq]

It's basically like as much as a state. Now these things will be drawing down the whole of the bitcoin energy is about 20 gigawatts if you look at it as well. Wow, that's about as much as all of Argentina is a 10 gigawatt power center. I think what's going to happen now though because you don't have the infrastructure, I think we're going to see massive solar and battery build outs and that's going to be super interesting. As you scale there. I don't know how else you're going to do it unless you have these small scale, literally nuclear reactors. In fact Microsoft has co opted like nuclear power everywhere so. So it's going to be power wars.

[Peter Diamandis]

Across the U.S. amazing. Here's our article on Nvidia investing $100 billion into OpenAI. There was a great CNBC piece that had Sam Altman and Greg Brockman and Jensen speaking together. Let me just quote what they say. This is Sam saying $100 billion is a small dent in the scale of our plans for 10 gigawatts of computer. This data center will be a multi square mile level of infrastructure. The stuff that will come out of this super brain will be remarkable. I love that. Right. Multi square mile superbrain. I mean tiling the world. And Greg Brockman then comes on and says we really want everyone to have their own GPU so agents can do work for you while you're sleeping. Which means that we're talking about on the order of 10 billion GPUs. The deal we're talking about with Nvidia is for millions of GPUs. We're still orders of magnitude off. We're heading towards a future where the entire economy is powered by compute and it's a future where it's compute scarce. Then Jensen comes on finally and says hey, this project is 10 gigawatts or roughly 4 to 5 million GPUs. That's approximately what putting into one project what we sold all of last year and double what we sold the year before and double what we sold the year before. So just massive increase. Dave, how you think about this?

[Dave Blunden]

Tie together those last few slides and really open your mind to the compute scarcity that's coming up. So you got $100 billion. The US venture industry is about 200 billion a year. And you hear you've got a single investment by a single company that's half of all a US venture in a year. Where's that going to go? It's going to go into buying chips and building data centers to support the users. Well, how many chips is Jensen going to be able to make? This year it's about 5 million.

[Peter Diamandis]

Yeah.

[Dave Blunden]

Okay, 5 million chips. This deal buys a lot of like, you know, 20, 30% of those by itself. Okay, well, when you looked at the other slide that Brian commented on on the X axis, wow, this stuff gets more and more intelligent and useful as you throw more hardware at it. How much more hardware? A lot more than we actually have on the planet. Like all these demos you're seeing, all these things, you're like this, you know, these benchmarks. There aren't anywhere near enough chips to deliver that to 7 billion people around the world.

[Peter Diamandis]

So we talked about, you know, where do you invest? I mean, so chip manufacturers, it's the construction to build out these data centers, it's the power plants to power these. I mean we're converting electrons into intelligence and into, into crypto. Imad, how do you think about this?

[Imad Mustaq]

Yeah, I mean, I think who controls this? This is the marginal producer in the economy, right. If you look at OpenAI's projections to get to 200 billion, 80 billion comes from this brand new AI agents line. And then other is another like 20, 30 billion. They're going to be rolling out AI workers that work around the clock. And then the investment, as you said, is a supply chain. But then it's also the companies that can have the expansion in margins because they have pricing power and they'll be replacing humans with AI and then downstream. The impact I think is going to be probably actually in the attention economy because it's about the only thing that isn't scarce is human attention. So we're going to look more and more towards media, which might be a bit counterintuitive.

[Peter Diamandis]

Interesting. Brian, as a builder, as a CEO and entrepreneur, do you worry about getting access to the compute you need?

[Brian Elliott]

You really want to be a player where everybody else wins when you win. And so you really want to be model agnostic, you want to be provider agnostic and you want to lift all ships. So I don't think if you are a sort of healthy player in the ecosystem, it is, it is a huge concern, but I think it's one. You can't be like fifth or sixth, right? You have to be the most important to these folks. And so this is like economies of scale are going to matter a lot. Here.

[Peter Diamandis]

Here's a chart reinforcing this lab. Compute has 3x in just one year. We see a graph showing OpenAI xai meta and anthropic OpenAI at the top. Xai coming on strong. We don't see Google on this or Alphabet, which is interesting. I don't know if any comments on this. I'm going to couple it with the next slide here, which is that data center capacity is expected to go up fourfold by 2030, going from 44 gigawatts to 156 gigawatts. 44 gigawatts today, 156 gigawatts by 2030. And from what I'm hearing that seems like a low ball estimate as well. McKinsey always low balls.

[Dave Blunden]

I think somewhere else in here we have demand is going up 10x year every year. Supply is going up very quickly, but nowhere near as fast as demand. So what does that mean? You see with all the model providers they're trying to offer fast or smart or whatever, but what it's really doing is rerouting your query to the smallest model that can answer the question to try and save some computer. Meanwhile they're all working on internal self improvement. So that's eating up a lot of compute at the same time. So you're starting to see the cracks in the supply demand curve here. Your question for Brian was a really, really good one. It's like do you worry at all about getting access? I think that a lot of the use cases that'll be deprived access are like the virtual girlfriend and doing your English homework because Brian can overpay 100x or 1000x over those use cases so he won't get cut off. But there is going to be a huge supply shortage for sure.

[Brian Elliott]

Yeah, it's about the marginal dollar, right? Costs are going to go up dramatically, I believe at the same time costs are depreciating from the actual cost basis to the chip. But the model providers are going to be able to increase cost if they're number one. And we're willing to pay that, we're willing to really pay anything because it's much more valuable what we're able to provide than these consumer type services.

[Imad Mustaq]

Economic value per flop is just going up dramatically because you're at this inflection point AI. Until a few months ago, most people were using GPT 4.0. It was like having a very smart goldfish memory buddy next to you that you had to oversee all the time. Now it's the set it and forget it and it can use millions of tokens, millions of lines of code and then be proactive. And as you know, Brian and Dave said it'll be the marginal dollar going up. But if we look at the previous one, like just put it in context, we had our Launch party at stability. I think three years ago, the Exploratorium, and it had a slide go up saying we have the 10th fastest cluster in the world at 4,000 chips, and now people are talking about 114,000 million chip deployments. The reason for that is literally just because of this economic thing. If you think the world of economic labor that you can do, that AI can do, has gone from maybe, I think, 1 or 2% now to to in the next few months, It'll probably be 50% in the next year, actually. And so this is all complete. This isn't a bubble. This is like, all very reasonable because your TAM has gone up. Your total. It's gone up so much. And so, yeah, it's going to be a crazy couple of years now with this. And there's just not enough energy, compute infrastructure, anything.

[Peter Diamandis]

Amazing. This is Greg Brockman on that very subject. I think part of the 2030 outlook is we will be in a world of material abundance. Right. I think that AI is going to make it much easier than you could almost imagine to create anything you want.

[Brian Elliott]

Right.

[Peter Diamandis]

And that will probably be true in the physical world in addition to the digital world, in ways that are hard to predict. But I think it'll be a world of absolute compute scarcity. And we've seen a little bit of what this is like within OpenAI, right? The way that different research projects fight over compute, or that the success of the research program is determined by the compute allocation. And so one thing we think about a lot is how do we increase the supply of compute in the world? We want to increase the intelligence, but also the availability of that intelligence. And fundamentally, it is a physical infrastructure problem, not just a software problem. Can you imagine the ongoing conversations inside of OpenAI and sort of the arguments about, no, I need the compute to do this project? Everybody's sort of vying for their own special crazy.

[Dave Blunden]

I don't know if you remember, Peter, but when we were at OpenAI headquarters a few weeks ago talking to Kevin Weil, I asked him anyway about the division of labor between him and Mark Chen and Sam and Greg Brockman, and he said, well, Brockman's out there just getting compute. We need compute like you. So he's just out there finding it. So, yeah, you know, I kind of miss the days when Greg and Sam used to do these things together. You know, Sam is on the road constantly now, so Greg has got to be in the house finding the compute. But he used to do a lot more podcasting. It was really nice when they were a two person team. But I don't know. Everything he said is exactly what you were just saying.

[Peter Diamandis]

The theme of today, abundance everywhere except compute scarcity. You know there will be some kind of a breakthrough on compute, right? And Iman, what's your bet on where we might get some sort of new breakthroughs at 10x efficiency or power use? Or is it going to be from quantum, Is it going to be from thermodynamic compute? What do you think?

[Imad Mustaq]

I think it's probably a data story right now. Like if you look at the Tonguey model by the Alibaba Quen, it's their AGI lab next to their Quen lab. They managed to score I think 22% on humanity's last exam with 3 billion active parameters with self reinforcing continuous learning model that runs on a smartphone. And they did it through improved data. Again, this thing David said about better rl better kind of thing. I think there's a data hybrid reasoning and other things coming together to optimize for specific tasks of the economy. Again, that 50% of tasks, that's how you could route this down to be highly efficient. And we don't know where the lower bound is on that because we could have more breakthroughs. We could have improved chip performance. Again, we're going up like five, ten times a year on chip performance and it's just very hard to extrapolate this. The only reason you can say it's going to reach this crunch point is simply because the amount of work that can be done in the global context is so large that at this inflection point there's no way that we'll be able to get them efficient enough. That's the only way we can kind of look at that.

[Dave Blunden]

If I could just riff on that for any of the entrepreneurs out there, what Imad just said is a really good barrier to entry if you work on it within your domain. So if you said, hey, there's all this technology and research related to transfer, learning and distillation that allows me to get the exact same quality of result with 1% of the parameters and therefore 1% of the computer, well then by all means do it. Right now we're all used to, oh, I can just get an AWS account tomorrow and I can just sign up and pay and it'll be there for me forever. It's like a utility. You know, that whole cloud computing era, they tried to convince us it's all a utility. It will always be there. Well, lo and behold, nope, it's A scarce resource. Greg just said it. He's always right. It's not a utility. Have a plan. Like you need a plan today. Because you know, Bill Gross was saying every mountain with a lake next to it has already been bought. You know, for, for pumped hydro power storage. You missed the opportunity to buy your mountain. Don't miss your opportunity to reserve your compute because it's now or never. Because these things get locked up very early. You know, this is a, it's a competitive world.

[Imad Mustaq]

Dave said 100 times, literally, if you have task specific data sets distillation and you have the right verifier, it is a hundred times difference in the cost of executing a particular task.

[Brian Elliott]

Yeah, this is a perfectly viable business plan. This is what happened with storage. If you. This is how Dropbox got so big. Right. They were the first folks to use S3 and not have to store, have their own data centers. And they were storage. There was a hundred other storage companies. They were just 10x cheaper than everybody else. And they scaled off of that and built a very powerful company. Same thing applies to models.

[Peter Diamandis]

Looks like OpenAI may get the shackles pulled off it. So OpenAI reaches a deal with Microsoft to allow restructuring from a nonprofit to a for profit. So OpenAI is targeting a $500 billion valuation as part of that. And I know what it's like to flip a for profit or nonprofit into a for profit. I did it with Singularity University many years ago. And you need to leave a certain amount of capital and capabilities inside the nonprofit. I won't go through the machinations of how you do it. But as they do this, OpenAI's nonprofit will be left with about $100 billion in capital. It'll be the largest nonprofit endowment out there, which is amazing what they'll do with it. You remember, Dave, we met with. I won't mention who it is at OpenAI. And they likely will be in charge of the nonprofit. And they have incredible vision for what they want to do to go and solve humanity's biggest problems with it. So if you guys remember, Microsoft invested $1 billion in 2019, another $10 billion in 2023, and they're estimated today to own about 30% of OpenAI. That's unconfirmed, but that's what the estimate is. And this sets them up basically to be able to become a multi trillion dollar company.

[Brian Elliott]

Microsoft can't lose.

[Peter Diamandis]

Microsoft can't lose.

[Brian Elliott]

Just for context on the earlier part of the conversation, OpenAI is twice the size of Harvard's endowment fund, which is for the longest time, been the largest endowment fund of all time. So from a nonprofit status, OpenAI in just a couple of years, doubling the size of the endowment.

[Peter Diamandis]

Fundamental. By the way, can you imagine the relationship between OpenAI and Microsoft right now? So, for example, when the Nvidia OpenAI deal was struck, Microsoft was notified the day before. Right. So OpenAI used to get all of its compute from Microsoft, and now they've been sort of kicked to the side and they're just growing unshackled. Fascinating.

[Dave Blunden]

Yeah.

[Imad Mustaq]

I remember when MASH s kind of had that commitment for 100 billion to open AI and then someone asked Satya about it and he said, well, I'm good for my 90 billion. I think that Jet Jensen is definitely good for his 100 billion. And, you know, like, now these are all crazy numbers, right?

[Peter Diamandis]

They are.

[Imad Mustaq]

When Microsoft invested 10 billion or a billion, we were like, we're like, that's big. Now it's like only 100 billion for the nonprofit, second largest. And we don't even blink at $100 billion being invested in them.

[Peter Diamandis]

Yeah.

[Imad Mustaq]

Because literally they will spend. They will have a trillion dollars of build out. And I think Elon Musk said something again recently. It was like, someone's like, what about Anthropic? He was like, they never had a chance. Because really, who can scale now to compete? Xai, Google, OpenAI and probably Meta, you know?

[Peter Diamandis]

Yeah. Speaking about that, this goes to our next slide, and the title here is Zuckerberg says better to lose billions than be late to superintelligence. So he's committed to invest 600 billion in U.S. data centers by 2028. Why? Because I don't want to be second to superintelligence. Crazy.

[Dave Blunden]

It's just staggering. The sheer size is staggering, but also the lives these guys are living is completely unprecedented in the world. I mean, Zuck was just at the White House a week ago having dinner with. Look at the table. Look at these people. And then they're all. The President is saying, how much are you going to pump into the US economy? And Zuck is like 600 billion. This has not existed ever in the world before. And I don't know, this next couple of years is like nothing in human.

[Peter Diamandis]

Sounds like inflation to me.

[Imad Mustaq]

The economy is dependent on its capital stock. You know, like, we build our universities, our factories and everything. But basically all this is, is it's the investment for the new economy. The economy 5, 10 years from now is run by AI it's powered by AI so it makes sense that you'll spend trillions of dollars on this. And these guys want to get it first from an economic point of view. But then there's more than that. Like, do you remember the story of how OpenAI got going with Larry? Larry Page from Google and Elon Musk, Larry Ellison?

[Peter Diamandis]

Yeah, yeah, Larry Page.

[Imad Mustaq]

I was having a discussion.

[Peter Diamandis]

I was there for that argument. And where Elon or Larry called Elon a species.

[Imad Mustaq]

Yes, Peter, do you want to, do you want to tell the story there?

[Peter Diamandis]

Oh, no, go ahead, go ahead.

[Imad Mustaq]

I mean, it's because they were discussing intelligence and Larry Page was like, you know, digital intelligence, he's like, can overtake humanity and that's fine. And he was like, no humans. Yeah, like Larry Page is on record. Not on record, but there again have been reports that he said he's willing to make Google bankrupt to get to super intelligence first. Like they weren't because they make so much money. But this is big stakes now.

[Dave Blunden]

I think it's worth just stepping back and comparing a day in the life of Mark Zuckerberg to Sam Altman. Sam has literally getting attacked constantly from every side, especially by Elon, while needing to beg for money from any source he can get it. Traveling all over the world trying to hold this together while becoming, you know, taking a nonprofit to make it into a for profit, which is a logistical nightmare. He's dealing with all of that. Zuck just needs to call his CFO and say, you know what, go ahead and divert that money back into data science and I'm going to go have a Mai Tai.

[Peter Diamandis]

They're printing money on my ship in the Caribbean.

[Brian Elliott]

The market will reward them for it too.

[Peter Diamandis]

It's an unreal existence. Dave, you said it right. I don't know how you remain grounded as a CEO of one of these companies when you're speaking about literally trillion dollar deals that you're in. I mean, it's crazy.

[Dave Blunden]

Yeah, that's a good concern too. I kind of trust the people that struggle have either struggled before in their lives or struggling right now. But you do worry a little bit about, you know, just the scale of power in a few people's hands and, you know, and what decision they might make tomorrow. But.

[Peter Diamandis]

But just to remind everybody, we are in a war footing. Going back to what you said a few minutes ago, Imad, you know, we're in a war footing, getting ready for the next economy. Just like we came out of World War II with a brand new interstate highways in the United States and aerospace and automobiles. We're gearing up for A new economy which will displace the old economy. And it'll be tens of trillions of dollars. Include robotics and will be close to $100 trillion over the course of a decade.

[Dave Blunden]

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[Peter Diamandis]

All right, let's look at what comes up next here. Dario Amadei on Claude designing Claude. This is a quote from Dario. He says Claude is playing a very active role in designing the next Claude. We can't fully close the loop, but the ability to use the models to design the next models is not yet going super fast. But it's definitely started. How long before it's going super fast? Imod.

[Imad Mustaq]

It'S the takeoff point right now. There was a recent interview with Tridao who is like the man for writing Cuda kernels on Nvidia. So he's at together AI and he came up with flash attention that literally increased performance 30%. He's like I use Claude code and I'm at least 50% better. And this guy is the cream of the cream of that. And we've seen that from top people already. That self recursive loop, it's coming inevitably. We're already seeing TPUs being designed by AI. And Sam Altman recently said, again, fantastic CEO, fantastic capitalist. But he said his plan is to get 1 gigawatt of new compute on every week with a fully integrated system that could also be training its own models. So I think we're moving full stack, vertically integrated like chip silicon, two model feedback loops and there's no way that won't speed things up even more.

[Peter Diamandis]

Can you feel the acceleration? Oh my God.

[Dave Blunden]

Look, I spent about six years of my life just purely building neural network and researching neural network algorithms and code and it's very Similar to discovering math, which Alex is always talking about. So Alex Wisner Gross on this pod is predicting, I think it was 18 months we'll be solving all math.

[Peter Diamandis]

Iman, you've been on this bandwagon as well, right?

[Imad Mustaq]

The AI is, I mean look at winning the gold medals in the ICPC and the Maths Olympiads and things like that. You parallelize it. Like we've been running 1000 lean provers in parallel analyzing things. You know, like next week we're releasing a full stack of economic proofs that you just can't argue with for everything. These AI is like once you actually apply them, it's not, it's not like you have one, like one genius is enough. But Dario said data centers of geniuses checking each other's work in parallel. Obviously you're going to get that next step up from that. And we've seen things like Terence Tao was formalizing some various proofs and they only got like 20, 30% the way in parallelizing that. I believe it was Morph Labs that did that. They managed to do the full proofs in like two days. So yeah, I think it's a good chance. I have no idea what the implications of that is.

[Dave Blunden]

Also remember Noam Brown over at OpenAI when we were there, was saying that their progress in core AI research is gated by compute now and not by researchers. They have a backlog of ideas. They just don't have enough compute to try them all. So pretty soon the AI will also be generating the ideas and then the backlog is purely compute. So that's where Elon is saying, well, I'll have the most servers, therefore I'll win the race. But it'll all be compute constrained. There's a window of a year or two here where it's also idea constrained. So lots of opportunity for people to think really hard during this window. But very soon it'll switch to AI generated ideas.

[Peter Diamandis]

10 billion here, 100 billion there. Pretty soon you're talking about trillions. So Alphabet becomes the fourth company, I like to call it, to reach the 4 comma club. This is to reach $3 trillion market cap joins Apple, Microsoft and Nvidia in this $3 trillion market cap club. Stock is up 33% in 20, 25 and 55% over the past year. I was talking about last time. For me, Google has been an extraordinary bet. Any comments here? I mean, I think the prediction markets still hold Google and Alphabet to be the long term winner. Imad, do you buy that still?

[Imad Mustaq]

I mean they're fully integrated with thousands of amazing talents. Denis at the head of DeepMind and they've got the reach. Right. So you started to see AI search results. It's not quite good enough because they're doing the crappy models. But when Gemini kind of 3 flash is better than Gemini 2.5 Pro. The directionality of where things are going again, they've got the full stack. They don't need to pay the Nvidia tax. They can build everything themselves and they have Metis cash. So why wouldn't they be up in the lead there?

[Peter Diamandis]

Yeah, yeah.

[Dave Blunden]

And just to add one thing to that too, we announced or we spoke about OpenAI doing their own chips with Broadcom, but they just started. Google's been working on their TPUs for years. So they're years ahead in that vertically integrated solution.

[Imad Mustaq]

They've been their own customer for a long time because they run the Google on the TPUs. TPUs are probably five times more power efficient than Nvidia chips and they have better interconnect for large context models as well. So they're pretty much ideal for what's coming through now.

[Peter Diamandis]

Nice.

[Dave Blunden]

How do you know that by the way? I thought that that's impressive knowledge.

[Imad Mustaq]

We use thousands of TPUs. We, we were down there when they didn't have jacks.

[Dave Blunden]

Oh, add stability. Y you had hands on access. Oh, no way. Yeah, because they've pulled them from the market effect because they're using them all internally now. So it's kind of hard to get performance specs. That's really useful information.

[Imad Mustaq]

Well, they might actually start selling them soon. We'll see.

[Dave Blunden]

We'll see if they can. Yeah, I'm betting I'll put a little money on. No, they won't be able to make enough of them. They'll eat them all themselves.

[Peter Diamandis]

Yeah, we'll see. There was a little video clip put out by Mustafa Sulaiman, the CEO of Microsoft AI which I found somewhat compelling. Let's take a listen to it.

[Imad Mustaq]

At the moment, these models are still one shot prediction engines. You know, you, you ask a question and you get an answer, you know, it produces a single correct prediction at timestep t and not they can't lay out a plan over time. And the way that you decide to go home this evening is that you know, you know, first to get up from your chair and then open the door and then get in your car and da da da. And that is just a computational limitation. And just as today there's a kind of super intelligence that is in our pocket that can answer any question on the spot. Like we dismiss how incredible it is right now is magic in your pocket. Now imagine when it's able to not just answer any question about poetry or some random physics thing, but it can actually take actions over infinitely long time horizon. Just that capability alone. I think that we basically have that by the end of next year.

[Peter Diamandis]

So I found that compelling. Imod Dave, what do you think?

[Dave Blunden]

I love the core point that look, this is absolute magic and it came into the world so quickly and there's so many ways to take advantage of it that we've only begun to scratch the surface. I do disagree that the planning ability, I don't know when this was recorded but the planning ability has gotten pretty damn good pretty damn quickly. So this might have been like three weeks ago, but today is different.

[Peter Diamandis]

Ancient history.

[Imad Mustaq]

I mean look, look. Do you think a Tesla can self drive from one side of America to the other 100%?

[Dave Blunden]

Yes. Yes.

[Imad Mustaq]

That's, that's planning.

[Peter Diamandis]

It's crazy.

[Dave Blunden]

Yeah.

[Imad Mustaq]

And then just think you hook that up with a vision model so it's making notes and it's writing the great American novel as it drives like again we actually have all the tools there and in fact, you know Brian, you're the expert in this, right? Like what have you seen in terms of. Yeah, massive long term stuff.

[Brian Elliott]

You can achieve AGI type effects at the application layer. This long term horizon of planning can't be done extremely well at the model level. But from a user or consumer who cares. It's about what I experience which is a long horizon plan given to me from a set of models. I would say we are in this reality today for a number of domains including software engineering.

[Peter Diamandis]

Nice. We had the CEO of Replit on the POD recently and I loved this quote about how to use agents. Let's take a listen. I'm one with true unique domain expertise. Let's say I'm a lawyer who is.

[Brian Elliott]

Top in the world at solving certain.

[Peter Diamandis]

Cases that, that are very rare. And so I have this domain expertise that I'm not going to share in the open source.

[Brian Elliott]

I'm not going to sell to scale.

[Peter Diamandis]

AI so that they can sell to, to OpenAI or Google all of those.

[Brian Elliott]

I'm just going to keep this resource to myself.

[Peter Diamandis]

But the way I would monetize it.

[Brian Elliott]

Instead of myself going and selling my.

[Peter Diamandis]

Services directly, I would like imbue this knowledge into an agent that becomes this very specialized agent in this very specialized.

[Brian Elliott]

Domain and then I can scale myself.

[Peter Diamandis]

So I like that one of the questions that we've had asked in the comments on this pod and we do read the comments from all of you listening or watching on YouTube is okay, you talk about what you should do if you're 18, 19, 21, what should you do if you're in mid career. How should you be thinking about AI? This sounds like a pretty good, pretty good example. Dave, how would you answer that? Someone mute.

[Dave Blunden]

Kirby. Yeah, that's a tough one. Maybe I'll bounce that over to you. Big brains on like the concept. I totally get like I've got domain knowledge, I'm a lawyer, I'm a doctor. You know, there's very, very specific domain knowledge all over the world. And I know the RLHF companies like Invisible and Merkor are killing it, wrangling all that knowledge and getting it into the models. So the question then becomes, okay, I wanna monetize that, but once it's ripped off my brain, they may pay me a lot for a month or two. But then what? Then I've just completely dumped my knowledge into the AI. Do I have any value? So I don't have a good answer off the top of my head for how to capture that. I would say there's no barrier to starting a company. You don't have to be 21 to start a company. You absolutely. There's so much greenfield opportunity out there and I do love these companies that have a regulatory barrier or a vertical domain deep tech, deep knowledge barrier. Just start a company using AI in that category. That's how you might then say, okay, now it's sustainable and I can, I can make a career out of it. So that's always a good choice. But you got to leave your day job and go do it.

[Peter Diamandis]

I would translate that to find a good problem that you understand deeply that no one has yet solved and go build around that problem.

[Brian Elliott]

There's never been a better time for these domain experts. I'm more bullish than Dave is on this 45 year old audience. And if you think about software has never been easier to build. That is true. But software is two things. One is sort of like I'd say the technical design and build of it, but you're imbuing a business process and a set of flows and decisions that you need a user to make. These insurance folks, these financial services folks, like they're world class at understanding how to do that portion of pricing products dynamically to the market. And that has very little to do with technology selection. So we can empower these folks with, with platforms like letc, to build large scale systems, enterprise systems that are purpose built for that 45 year old insurance underwriter or financial product person. And this has never before been possible.

[Peter Diamandis]

Yeah, yeah.

[Imad Mustaq]

I've been thinking a lot about this and you know Nassim Taleb, the black swan guy has this great thing concept called intellectual yet idiot about very well credentialed people who just don't have any skin in the game. So they don't give a damn. Right. That's a flaw of many of our systems. AI models are intellectually idiot. They don't give a damn. One of the most important things is actually giving a damn about the context, about when these are implemented. And if you think about the long tail of these implementations to solve problems, if you actually give a damn and you can communicate it and be that intersection, that's where you get the most leverage. You actually need to understand the consumer and how they operate today. You need to actually have some skin in the game in the way that you do that. And, and I think people underestimate that because we just assume the technology will sweep because people do these analyses and they understand the way we do. No, there needs to be that translation layer and you need to actually be able to communicate and show that you give a damn.

[Peter Diamandis]

So your advice Imad, to that 40, 45, 50 year old individual who's like how do I apply AI to do something significant in my life?

[Imad Mustaq]

I think that when you look at the problem there is the intellectual part. Hey, I've got cognitive surplus now from these tools. But the next part is getting to understand the organization that you're in. If you're within your organization, trying to improve it, the real like things and balances and who you need to communicate these things to in the appropriate way. And then if you're servicing someone having that really high touch consumer aspect of it where you're helping them through something that's very scary and has huge potential, will pay a massive amount of dividends. And again you can use the AI to help you communicate and things like that as well. That human touch I think is underestimated, particularly as we again diffuse from just the early adopters to the vast middle of this industry.

[Peter Diamandis]

Yeah, we're just at the beginning of this game.

[Dave Blunden]

Well, Peter, that video was Amjad Massad. Do you want to tell the story about how easy it is to build software from?

[Peter Diamandis]

Maybe so you know, I was flying from Santa Monica up to San Francisco to Stanford. Dave was already there and we were interviewing and Saleem was there too. We Were interviewing Amjad about Replit and you know, I had downloaded Relet but I'd never really used it. And so like, damn if I'm not going to give it a try. So I have StarLink on my SR22 Turbo, my airplane. So I'm flying the airplane on autopilot. I've got the Starlink antenna in the front and I plug into Replit and I coded up a Mindset app on the flight there and it was fantastic, right? So it was like, that was so easy, you know, zero requirements. I just needed to know the single most important thing again, if you're new to this, if you're just a fan of this, if you haven't played at all, right, Replit's amazing. There are other platforms lovable and others. It's critical for you to just try, just try and play and bring a curiosity mindset, your playful mindset. And if you know what you want to exist, the AI systems will help you get that into existence.

[Dave Blunden]

And it's only going to get easier. Your domain knowledge will be extremely important. And the product creation use blitzy. It'll be easy, easy, easy.

[Peter Diamandis]

So before I drop, before I move past the conversation about Replit and Vibe coding, Brian, you're taking this level of coding to a brand new level. How do you apply this to industries, to entrepreneurs? What are your thoughts?

[Brian Elliott]

There's two classes of software, right? There's this disposable widget based software that Peter, you built with Starlink on your plane, right? And this is the idea of getting this concept into a prototype. And then there's true enterprise scale software. I'm going to have thousands or hundreds of thousands of users. I'm going to have concurrency, I'm going to have good caching, right? And that's the part of the system where Blitzy fits in. And so everyone's having this Peter experience, right, where I can create something quickly and then they're getting to the enterprise scale and they're getting none of those gains, right? And so we've brought the vive coding speed to the enterprise scale and we can do that for the new entrepreneur building the insurance product or we can do it for the existing enterprise that's doing large scale development. But the idea is like velocity from an engineering perspective is dramatically higher than it's ever been. So it's never been a better time to build.

[Peter Diamandis]

Do you interface with mid level managers and companies or is this got to be a top down for people who want to use Blitzy to sort of improve their product? And capabilities.

[Brian Elliott]

Yeah, anyone that leads a large engineering team comes and works with us. So lots of times CTOs and CIOs will come me directly. But you also have, you know, VPs of engineering that say, I'm going to make my company go faster and I'm.

[Dave Blunden]

Going to weigh in and I'm going.

[Brian Elliott]

To bring Blitzy in and be the first to do it. And we love those folks too.

[Peter Diamandis]

Got it, Got it. Great. Here's our next one. Comes from Andy Jassy, CEO of Amazon. He's like, wait, wait, wait, we're going to build glasses too. Meta is not going to lead the way here. There's got to be someone else. So Amazon is developing their own AI glasses to challenge Meta. And what I found fascinating is that these glasses are going to be. There's a consumer version, but importantly there is a version that's going to be used by their drivers and the drivers are going to be recording everything. And for what use? It's to train the future robots. So this is codenamed Jayhawk, expected to launch in late 2026 or early 27. And today the company plans to pilot 100,000 units by Q2 for its workforce of 390,000 drivers. So, Iman, I think you said something about this earlier, right? This is how we're going to get the data to train up new systems.

[Imad Mustaq]

Yeah, I mean, it's kind of obvious, isn't it? You're going to have seamless data to train up the robots of the future from these kind of fleets just as to replace the workers of the future. It will just scan all your slack messages and code commits and create a virtual version of you. Yeah, but the reason is the technology is good. You know, it's been 11 years since Google Glass. I think it was 2014.

[Peter Diamandis]

Wow.

[Imad Mustaq]

You remember that? They look stupid at the time.

[Peter Diamandis]

I remember that.

[Imad Mustaq]

Now. The new Meta glass, yeah, they work and they are useful and they are light. So how can you do your job now without being augmented? I think this is going to be the next part and it just feeds back because the glasses and the guidance will just improve until it's perfect. Almost.

[Dave Blunden]

I love it when Ahmad says it's kind of obvious. Just like when Alex answers those like humanities last exam questions, like, oh, it's four, of course.

[Peter Diamandis]

Well, you know, competition is great. You know, we've seen there are a number of companies creating glasses, there's xreal and others, but it's really to productize these and make them smart, so cheap and so consumer friendly that they Become. I still remember the first time I saw someone walking down the street with an earpiece talking to themselves and I was like, is that person crazy or what's going on? I don't know if you remember that experience. The first time you ever saw somebody with the equivalent of what is now an AirPod. And we're going to start to see people walking around with glasses. We talked about this in the last podcast. Are you going to be comfortable with everybody recording you all the time? I think in the beginning you will not be comfortable, but then it will just be assumed you're always being recorded. The idea that privacy exists is going to be a long lost concept. I don't know if you guys disagree with that.

[Dave Blunden]

I think it's interesting. No, no, no, it's definitely. Yeah, it's a long conversation. But what's really interesting to me is that of the Mag 7 today you have three secondhand CEOs. Andy Jassy being one of them. Now Amazon is the best managed company, I believe, in the history of the world. And we teach all of our executives and Our teams the OP1 planning process that Jeff Bezos and Andy Jassy invented. Incredible company. But you've got three legacy CEOs, Andy Jassy. So you got Apple, Microsoft and Amazon. And then the other four are founder led CEOs.

[Peter Diamandis]

Well, no, I mean you've got Satya, you've got the CEO of Alphabet, right?

[Dave Blunden]

Oh, Sundar Pichai. Yes. So you got four. Four. Okay, so four second hands and three founder CEOs. You're right. You're absolutely right. Yeah. So it is interesting because here you're like, hey, we're going to do glasses too. Or Apple's like, oh, we're going to add AI to our products too. Okay, that's not exactly, I mean, listen.

[Peter Diamandis]

You know, founder led companies are able to make much more, more dramatic right hand turns and say to the shareholders, listen, I've made money for you before. Just believe me, this is what I'm doing. Like it or not, Elon does that every single day. We're seeing Meta do that. Anyway. All right, onto our next subject. Albania appoints the world's first AI made minister. So I find this fascinating. I think we're going to have more of these in the world. The goal of this AI minister is to tackle corruption in public tenders through fast, efficient, impartial decisions. Imad, you and I have talked about this a lot. Both of us are part of the, in fact, indebted to you as well. Part of what's going on in Riyadh and Saudi. At fii, we're going to be meeting with ministers talking about how to use AI to run their policies and their governments more efficiently. How do you think about this, Iman?

[Imad Mustaq]

Well, I don't think anyone thinks. Is there anyone listening in here which thinks that she won't do a work, she won't do a better job than the existing ministers? I mean, like, this is kind of the bar. I think, again, this is inevitability. The AI will incorporate more and more of our decision making systems and be representative of us until it makes those decisions because it will do a better job. And the question is just how and why will that happen? I have to say though, in the launch video there was a bit of creepiness because she said, I'm very disappointed at how people have perceived this. Now it's either a person telling her to say that, which is one thing, or the AI itself is disappointed, which is another can of worms.

[Peter Diamandis]

Yeah. So the real question, of course is if you've programmed or you've stood up an AI minister, what data have you provided to it, him or her? And is there a bias in that data? Does the person who controls, you know, the data center control what the minister is going to do? Can you inject it? I mean, there will be a lot of debate about the impartiality of these ministers. Like it or not, we are humans.

[Dave Blunden]

I spent my early childhood in Iran and Brian spent a fair amount of time overseas too. And, you know, the global standard is corruption. You know, areas that are not corrupt are extremely rare on a global scale. Albania being one of the worst or among the worst. And this is just going to be nothing but good. Even if it's not perfect in terms of its ui, it doesn't matter. It's not going to deliberately take your money or ask you for a kickback or a bribe. And that's just such a global game changer. So, sorry, Brian, you were going to say similar.

[Brian Elliott]

Like the hurdle rate for success is so incredibly low. So I think the AI could be right 80% of the time and it would be better than the current status quo and it would sort of be randomly messing up as opposed to sort of purposely driving money to a family member. And so it's only gonna get better. So I think this is probably a great thing for Albania.

[Peter Diamandis]

Yeah. All right, our next segment in our WTF episode today is energy robots and transport. Here we go. Listen up to our US Secretary of Energy. I don't agree with what he has to say. But let's, let's hear it. So Elon Musk has it completely wrong. He has a wildly exaggerated view of where solar and batteries will go. And I'd like if we could make a bet 50 years out, I'll make a bet solar never gets to 10% of global energy. Okay, let me give you some, let me drop some knowledge on you. So today in the United States, there's 18 gigawatts of solar capacity installed in the first half of 2025. Solar accounts for 50% of new electricity generating capacity in the first half of 25 and 69% in the first quarter of 2025. Solar has made up 10.2% of the total US installed utility scale generated capacity in 24, surpassing nuclear and hydropower. It's now the fourth largest electricity source after natural gas, coal and wind. Gentlemen, I'll mention one other thing. Nrl, which is the National Renewable Energy Laboratory, which is under the Department of Energy projects, Solar could power 40% or more of U.S. electricity demands by 2035. So I think he needs to talk to some of his labs.

[Brian Elliott]

Yeah. The historic challenge with solar has always been storage. Right. Which no one's better at that than Elon. And when he's built at Tesla, solar is intermittent source. And so you'd store it over time and there'd be some depreciation on that storage. But that's essentially a solved or nearly solved problem. And so yeah, Chris, is solar is a big deal. Storing solar is getting easier and easier and the DOE is absolutely correct on this.

[Peter Diamandis]

You know the other thing I would.

[Imad Mustaq]

Write about solar then go ahead. Right. About solar. There's no way the US can keep up with China.

[Peter Diamandis]

Yeah.

[Imad Mustaq]

Solar is basically the US's best shot at keeping up with power.

[Brian Elliott]

The hard part of the mod is our solar supply chain is completely tied to China. So it's not about does solar work or is storage going to get better and better. It's getting better every single year and Elon's driving that. It's can we have a US driven solar supply chain or we're not reliant on an outsourced partner for what's going to be one of the most important ways for us to capture energy.

[Peter Diamandis]

I think that's a great point. Exactly. It what you know, we do need to realize the world is about to change on the back of asi.

[Dave Blunden]

Right.

[Peter Diamandis]

We're going to have better manufacturing processes, we're going to have new materials, we're going to have all kinds of capabilities that did not exist today, but will exist in three or four years. Can we scale it quickly enough? We'll see. But China has run circles around us. The numbers are pretty staggering. China leads with 880 gigawatts of solar capacity in 2024, growing at 45.6% annually. That's insane. The US is 177 gigawatts growing at 27%. So they're basically lapping us constantly.

[Dave Blunden]

No, you're so right, Peter. We have a fundamental structural problem because look at all the companies that we've built. Ahmad, Brian, all four of us, they're all like, I need 3, 4, 500 grand of seed money, then I need a couple million bucks. And then if all goes well, it's going to be worth billions of dollars. That's pretty damn compelling from an investor point of view. But when you start talking about industries like real industries like automotive or solar energy, we're just not making the investments. We have a fundamental structural problem in the country that prevents us from making those investments. And the $200 billion a year venture community is never going to do it and isn't even nearly big enough to do it anyway. And so what happens every time with 80% of the world's cars were made in Detroit? 80%. Every part of those cars was invented in America. Yet we lost the entire industry. It almost died completely. Obama had to save it from absolute collapse. And now it's kind of coming back. But why? How does that happen? And it happened with LCD TVs. It happened everything. It's all invented here, cloned elsewhere. They make the investment to do it at scale, to get the cost down, and then they bring it back into the us back into Europe at low.

[Peter Diamandis]

Prices with their large tariffs.

[Dave Blunden]

It's just a fundamentally broken machine in the US That's. Well, tariffs are part of that.

[Imad Mustaq]

Well, who pays the tariffs?

[Dave Blunden]

Right?

[Imad Mustaq]

It's consumer. I think that when China gets its robot supply chain going, it's only going to widen because those robots are going to build those factories.

[Peter Diamandis]

Yep, huge lead there.

[Dave Blunden]

This is a big focus area for David Siegel, you know, the two Sigma founders. So if we want a pod with him, he'd love to riff on this topic, but he has some ideas on how to fundamentally fix them.

[Peter Diamandis]

Yeah, so we reported last pod about, about Brett Adcock's, you know, figure raising a billion dollars at a $39 billion valuation. I mistakenly said it was a $93 billion valuation. Sorry to triple your valuation there, Brett, but it was 1 billion.

[Imad Mustaq]

He's underwater Just give it a few weeks.

[Peter Diamandis]

Exactly. It's 1 billion on top at a $39 billion valuation. Pretty amazing. And Brett is an incredible entrepreneur who was in the EVTOL with Archer Aviation before and has brought his engineering expertise to the table. They've also announced a strategic partnership with Brookfield. Brookfield is giving them access to 100,000 homes, 500 million square feet of offices and logistics space. There is a concept right now. We learned about this when we were visiting Bernd at 1X Technologies. These companies believe they need embodiment of AI to really get to AGI and beyond. They need to be in different places. And what Berndt was saying, if you remember Dave, was if you're in the factory building automobiles or distributing packages, you're seeing the same thing over and over and over again. You're not getting diversity. So we need to be in the home, in the office, like a toddler, crawling around and getting you data all the time. Thoughts?

[Dave Blunden]

Yeah, it's totally right. I don't believe that you need that to get to AGI. I heard burger burnt say it. I think you can have AGI without that. But if it wants to understand your daily life, what it means to trip over the kids blocks and bump your head, it needs this data to be empathetic and understand that part of life. But you can have AGI without that. Nevertheless, this is exactly right. You need all that kinematic telematic data to build the true motion AI foundation model.

[Brian Elliott]

Yeah, and it's these models are inferring physics based on video data. And so it's incredibly hard when you're faced with the real world. And so when Brett shifted off of his OpenAI partnership, you know, 18 months ago, he made this very, very assessment, which is we have to build our own foundation models that are focused on our own data from real world simulation. Because, you know, inferring physics is insufficient.

[Peter Diamandis]

For an LLM and not to be left behind in the robot world. OpenAI is ramping up their robot work. It's like, wait, wait, wait, no, we need robots too. So OpenAI was in the robot space back in 2021, but they basically paused all of that to focus on ChatGPT. And today they have listed a number of postings for jobs on teleoperation simulation, mechanical engineering. So if you're listening to this pod and you want to build robots, go check out OpenAI's open roles. Of course, this is a multi trillion dollar marketplace. Here's the interesting thing. Morgan Stanley always looking at these reports and all the Reports by these banks are so conservative, they're saying it's a $5 trillion market by 2050. When I'm looking at the numbers. Vinod Khoslo was on stage last year at the Abundance Summit. And then we had Brett. And the low end of this is a billion robots by 2040. The high end, and Elon makes a convincing argument, so does Brett, that we're at 10 billion robots by 2040. So if we're just at a billion robots and they're 25k each, that's a $25 trillion marketplace by 2040. I don't know why these guys are low balling these numbers anyway.

[Dave Blunden]

I'll tell you one thing, when you read the way they analyze this, they use the old business school kind of just project it forward garbage without any concept of either self improvement for software or self manufacturing for robotics. Yeah, but that feedback loop dominates the math in the real world. And that's why they're way, way off in their projections.

[Peter Diamandis]

For sure.

[Brian Elliott]

It's the classic, like Uber's market size being the same as taxis. Like, it's. It's. It's so flawed.

[Peter Diamandis]

Great point, Ryan. For sure. Everybody, there's not a week that goes by when I don't get the strangest of compliments. Someone will stop me and say, peter, you've got such nice skin. Honestly, I never thought, especially at age 64, I'd be hearing anyone say that I have great skin. And honestly, I can't take any credit. I use an amazing product called OneSkin OSO one twice a day, every day. The company was built by four brilliant PhD women who have identified a 10amino acid peptide that effectively reverses the age of your skin. I love it. And like I say, I use it every day, Twice a day. There you have it. That's my secret. You go to Oneskin Co and write Peter at checkout for a discount on the same product I use. Okay, now back to the episode. All right, I want to jump into the economy and Imod Love having you here on this and excited when you announce your economic treatise. I'm still predicting Nobel Prize for you, buddy. That's my goal, nothing less. Nobel Prize in Economics. And then we'll do a Nobel Prize in something else for you as well. So here's the slide. It says AI is not a bubble. Dave, do you want to lead this description here?

[Dave Blunden]

It's not a bubble. Look at the slide. It's clearly not a bubble. God, I'm not. I really want you to rip on this, but look I was there, I was alive. I was actually building companies during the bubble that, that's changed the course of my life.

[Peter Diamandis]

The dot com bubble to be specific.

[Dave Blunden]

Also did. Oh yeah, yeah, not the tulip bulbs back in 17. All right, so 16, whatever. Yeah, no, the look, I was on the board of MicroStrategy. Check its history. You know, strategy.com got up to like a $14 billion valuation I think with no revenue or certainly near no revenue. This is not like that at all. Look, look at the red line on the right.

[Peter Diamandis]

So just to describe it for our listeners, this is a graphic of Cisco showing its stock price going from 100 bucks up to around 700 bucks. But at the same time its stock price is peaking, its 12 month forward earnings per share is pretty flat. So that's by definition a bubble. It's a hype bubble. On the other side of this image we see Nvidia and what we see is that the price of Nvidia is going up and it's going up lockstep with the 12 month forward earnings per share. It's generating real revenue, real profits. So Imod smack us with some knowledge here, buddy.

[Imad Mustaq]

Yeah, I mean I think stock market is a bit of a voting mechanism in the short term and calculating mechanism in the long term. What we see with these bubbles is it can be disconnected, the fundamentals. But the real thing here is AI is useful. People pay for it because it has economic value. That's why even when you look at $100 billion of Nvidia money going into OpenAI, that feels like back in the dot com bubble we had this round tripping of revenue but it never created economic value. Every single GPU that OpenAI uses will be booked out because it can do so many things economically. And that's why this is not a bubble. It's a transition from one type of economy to another type of economy. And I think that's what a lot of people just haven't figured out. And this is before we see that inflection point of what Mustafa talked about earlier, what Brian's working on, of this incredibly long term kind of planning agent capability that can do really complicated stuff. So I think this will just continue. There will be some weirdness. And when your kind of taxi driver starts talking about generative AI digital assets, that's when you probably know that it's going to be above all.

[Peter Diamandis]

Yeah, when, when your mom starts talking about should I invest in this company? That's crazy.

[Dave Blunden]

Well, just some numbers, just because it was a part of our lives or part of my life. The hottest company in the world by far was Yahoo, back in the Internet bubble. And it's hard to imagine that now, but Yahoo was the dream of all dreams. And it went public at a $300 million valuation. Laughable. And then on day one it got to a billion dollars. It was trading at a billion. The press went like crazy, like this. That's insane. It has less than 100 employees. How can it be worth a billion dollars? That's nuts. So then after that they got super acquisitive, bought a whole bunch of assets, got all the way up to about 110, $120 billion valuation at the peak of the market there. And then the capital got cut off almost overnight. And then 911 happened and the market imploded. So it went down 95% and then pretty quickly after 911 recovered again and settled around asset value, so around $50 billion. Okay. So then not much happened after that. Eventually got acquired, whatever, gone. So Jensen now is on top of the world. He's investing $100 billion into OpenAI, buying everything, which diversifies that value. $4.5 trillion valuation. So not only are the revenues and the earnings very real at Nvidia, but they're also diversifying and aggregating power and equity stakes at an incredible clip. So you know it is priced to perfection. That's also true too. But the foundation here is very real. Nothing's going to change the world more than what's going on right now. It is definitely not a bubble. It's not even vaguely like a bubble.

[Imad Mustaq]

There's one way you can tell a bubble and that's when people come up with brand new statistics like Yahoo is valued per eyeball. So if Nvidia is a transistor, then we know there's an issue that's Ryan.

[Brian Elliott]

I think people miss the latency between the capex involved in creating the Internet and the value that came out of the Internet. Right, the dot com bubble, like by any means, if you dollar cost average in the year 2000, even the height of the bubble and then waited 10 years, you had fantastic outcomes. Right. But the latency between capex right now and earnings is almost immediate. Right, because they're able to translate that. All of the advertising engines are able to translate it almost immediately into additional earnings. So this is just a timing and the timing for AI, basically payback is immediate.

[Dave Blunden]

By the way, I want to double down on what Brian just said because I thought I was the only guy on the planet saying this. There was no Bubble. The Internet changed our lives more than anything in prior technology. What it was is a catastrophic loss of confidence in our own investment community. And then 911 happened right in the middle of it and we just lost faith in what turned out to be the best investment. And that's when Google was born right in the bottom of that Amazon.

[Brian Elliott]

To Iman's point, it's a voting mechanism. Right.

[Peter Diamandis]

Let me remind our subscribers, these charts that we're going over, these slides are available to you if you go to diamandis.com wtf. Go there, download them. As I said before, have a conversation with your favorite AI, you know, large language model about this dive in. This is the fun stuff. This is what Dave and I do all the time. Iman just knows all this stuff cold and I'm sure Brian does too. So yeah, I got the two minute.

[Brian Elliott]

Heads up on this podcast. But hey, it's been so fun.

[Peter Diamandis]

Yeah, well, you got two minute heads up and IMOD got 30 seconds. So there you go. All right. But I love having brilliant people around us that we can have these conversations with. Yeah, I put in a good 20 hours. Yeah. All right. I want to have a conversation about this. Maybe a little bit of a debate here. So Eric Wan, the CEO of Zoom, said we're heading towards a three day work week that will come on the heels of AI. Let me give you a few other quotes here. So Bill Gates, his quote is a reduced work week to two to three days will happen within a decade. Jensen has had a four day work week may become the standard. Jamie Dimon from JP Morgan has said future generations may work 3.5 days weekly. I like the 0.5. You know, didn't want to say 3, didn't want to say 4. 3.5 thoughts on this? I mean, you know, Dave, you and I are talking about 997. I don't know about you, but I am working. Actually I get up about 5am so I'm more like 6am to 8pm yeah, seven days a week. It's exciting. I don't want to let a day go. It's like this is fun. Three day work week.

[Dave Blunden]

Yeah, I totally agree. I mean it's just hard not to work constantly because it is fun like you said. But there's so much, I mean just keeping up with everything going on consumes a full week work week and then you have to produce on top of that. So I'm seeing a lot of divergence here. You've got all these people that I know around here that are working996,997 just is crazy. And then we're predicting that workloads will go down for everybody outside the building, apparently. But it's not clear to me how that works. Like if, if I'm doing something and then AI can do it better, why would I be doing it three days a week? You know, what does that, what does that achieve? So I don't know, you guys.

[Brian Elliott]

If a human is providing like economic value, that's driving up the value of the company and it has some relation to the amount of input that they put in. They're probably going to work as much as the company will force them to work. Right? Like five days, six days, seven days. Because they're ultimately competing with some other firm. So either they don't need the human at all or they can have somebody for five, six, seven days a week. And so the in between doesn't really make sense because you're competing against other folks that aren't going to make similar decisions.

[Peter Diamandis]

Imad, what's your thought?

[Imad Mustaq]

They're all going to get government jobs. I mean seriously, like again, humans will have negative value in cognitive labor in a few years.

[Peter Diamandis]

You've said that. I want you to double down on that conversation. It's a really important concept where humans have negative value in the equation. What does that mean?

[Imad Mustaq]

You're working on a team and you're the dumbest person on the team. You drag it down. You're working on a team with AIs. The AIs are smarter, more capable than you, they never sleep, they learn perfectly from all their mistakes and they can take in 10 million tokens or words at one point. You're not going to be able to keep up. So what does that look like? Okay, we might create new jobs. No one's really been able to articulate what they are, you know, apart from entertainment and a few other things. So you look at the 1929 emergence, you have jobs programs, you have an expansion of the public sector and more. Maybe we figure out taxation. But I think when you look at a three to four day work week, your job is your identity, it's structure and it's more. You can't just have people unemployed. So I think they will have jobs programs and others with a three, four day work week giving some sort of Social Security net. And that's what it kind of looks like. Because if you're in a job where your role is to beat other people, as in private sector competitive jobs, particularly in knowledge work, you're not going to beat an AI. And then in a few years your muscles aren't going to out compete or your skill at plumbing isn't going to out compete a robot.

[Peter Diamandis]

So just to give two examples on this idea that humans drag down the average and have a negative impact on value. This is where, for example, if you have self driving fleets and a human enters that and drives that human is likely to have more accidents in the self driving fleets. A stat from about six months ago, there was a study done out of Harvard and Stanford in the medical space and it looked at physicians diagnosing versus physicians with GPT4 versus GPT4 on its own, the numbers were insane. So a physician diagnosed 74% of the time successfully on their own. In this particular study, physician using GPT4 bumped up two points to 76%. But GPT4 on its own was getting it right 92% of the time. So the human in the loop was actually doing damage. We're biased. We're not able to have pure thought and decision making there.

[Imad Mustaq]

Actually, I think we've got to start here. If all cars were driven at Waymo level, we'd save 40,000 lives a year and a trillion dollars in societal costs.

[Peter Diamandis]

Hmm. Amazing. Yeah, amazing.

[Brian Elliott]

This, this sort of, this, this staff from Eric misses the organizational point about just having fewer people. So I think we're gonna see there's this number called the Dunbar number, which is like 150 people is sort of the max amount that you can have in a network in your head without having lost all the folks. So it's likely we're gonna have a bunch of organizations of about 150 people because the 151st is actually negative and it costs communication no matter what. So you max that out, use all the AI you can to sort of like get the jobs to be done thrown into the economy through your organization.

[Peter Diamandis]

Yeah, yeah. So curious about this one. We talked about Duolingo a few pods ago, especially because of the breakthroughs coming out of both OpenAI and Google. So Duolingo CEO says AI made employees four to five times more productive. No layoffs reported, no full time layoffs since the company went AI first. And AI has sped up lesson creation in languages, math and music. And Duolingo raised revenue forecast to 1.02 billion from 996 million. Dave, what do you think about this?

[Dave Blunden]

Well, one thing I can say for sure, just based on these last two slides, if you look at podcasts and interviews from maybe three or four months ago, they're very, very honest. About job displacement and job loss. All of the big wigs now are switching to, oh, it's going to be great. There'll be a three day workweek, it'll be fine. And here, hey, we used AI everywhere, but we didn't have any layoffs. I think that everyone is now worried about wholesale panic and pitchforks in the streets. And so they're not being particularly honest about the way they see it. Now, that being said, there's going to be massive amounts of abundance. There's more than enough success and happiness to go around, but there is no mechanism right now for distributing it. It's going to land in like 5 or 10 or 20 hands or maybe a few more than that, but a very concentrated subset if things just evolve with no change. And that's just the reality of how things are evolving. And yeah, occasionally a company will grow so quickly that there are no layoffs, but many, many other companies are going to say, wow, half the headcount can go because I, I AI'd it. So, you know, I'm just seeing a lot less honesty in these interesting, these interviews.

[Imad Mustaq]

DuoLingo is growing 30, 40% a year. It should be growing its employee base 30, 40% a year.

[Peter Diamandis]

Yeah, interesting point. Yeah. So it's standing, it's standing still. Well, this is what Marc Benioff talked about as well. You know, we're growing, but we're not growing the number of engineers with agent, agent force there. I thought this was important for us to talk about. NASDAQ pushes to launch trading of tokenized securities and so the US to become the first exchange to move with this initiative. And you know, it's not enough for us to trade five days a week, you know, eight hours a day. We want to go to 24 hours a day, five days a week and then it'll be 24, seven. So if approved, we'll see the first tokenized trades roll out by late 2026. As a reminder, Robinhood, at least their EU version in June and July started launched with tokenized stock tokens for 200 US stocks. They've been trading 24. 5. And Robinhood, also on their EU platform, rolled out stock tokens for private companies OpenAI and SpaceX. So I found that pretty fascinating. It hasn't come to the US yet, but it most likely will. Thoughts about this, Dave? You just been trading successfully on the.

[Dave Blunden]

Actually there's another one this week, Better mortgage out of nowhere. You guys can look it up betr you can check it out.

[Peter Diamandis]

What is better mortgage?

[Dave Blunden]

Well, so better Mortgage is one of many companies, including Go Health and one I'm involved with as chairman, that if they implement AI correctly and their workflows have huge instantaneous lift. And Better Mortgage is a great case study. So Better Mortgage is an online marketplace for mortgages. They swapped in AI workflows and AI voices. It works really well. Nobody's paying attention to these micro caps. So they trade very cheaply with virtually no liquidity. No mutual fund can touch them because there isn't enough float anyway. It's. It's AI.

[Peter Diamandis]

At some point I'm writing it down.

[Brian Elliott]

Noticed Better Mortgage just make the trade live. Peter, get on Robin.

[Peter Diamandis]

Yeah, one second, I'll be right there. Okay.

[Dave Blunden]

There's a whole theme there, though. You could probably query them up relatively quickly. So all you want to do is look for companies that have huge amounts of consumers passing through their pipes. Any type will do. And then look at the management team and say, is this management team going to AI this or are they going to miss the window? And if it looks like people that will AI.

[Peter Diamandis]

This is not.

[Dave Blunden]

Lots of.

[Peter Diamandis]

This is not investment advice. I'm supposed to say that every time we mentioned.

[Dave Blunden]

It's just a thought.

[Peter Diamandis]

But. But I'm curious about this idea of, of tokenized securities. I mean, we're heading towards a world where everything's tokenized and our agents are going to be trading them for us.

[Dave Blunden]

But we desperately need this too because, you know, going public is very, very onerous and getting more onerous all the time.

[Peter Diamandis]

Oh my God.

[Dave Blunden]

Yeah, but companies are getting created and growing faster than ever before. There needs to be an easier, shorter, closer liquidity pathway and some kind of reliable, trustworthy, token based, pseudo IPO would completely open up the economy. It would solve a lot of the problems we talked about earlier in the podcast, actually. So this could be the structural change we really, really need to bridge the gap between, you know, early stage venture and then IPO, which is only accessible above, you know, 2100 billion now.

[Imad Mustaq]

I mean, US monetary velocity is not really recovered since COVID It's still below the decade below Covid. Crypto is legal in the U.S. apparently, GDP is going on the blockchain. The Treasury Secretary said, whatever that means. Like, if you want to see what a bubble looks like, just look for the next three years in digital assets. That will show you completely what a bubble looks like. Generative AI is the proper thing. This one will be insane. I think you'll be able to trade stocks on X by next year. Everything is a go. In fact, you'll see blockchains. From Stripe to Amazon to Google, everyone is launching their own blockchains now because finally, it's legal.

[Dave Blunden]

Totally. Right. And not to get too technical, we can cut it out of the podcast if it gets too technical. But historically, the reason the IPO market exists is because it's massively regulated by the sec. And you have all these GAAP accounting standards and you have to.

[Peter Diamandis]

Do you want to prevent widows and orphans from losing money in deals?

[Dave Blunden]

Yeah, yeah. And so now all of that.

[Peter Diamandis]

And you want to employ. And you want to employ enough lawyers.

[Dave Blunden]

And you want to employ enough lawyers and. Yeah, and accountants. It's the biggest governing lobby thing in the world. But the AI can do all of that now. So you could. You could have a perfectly fair and valid reporting system that is on the blockchain that is far better than what the SEC currently does and what your 10Q reports currently do. In fact, your 10Qs are so full of legal garbage, they're almost unintelligible without AI Anyway, so why not make this all seamless, Move it to the blockchain. It goes. All right, into ETFs. Anyway, there very much is a solution in there. It's really a good idea.

[Peter Diamandis]

All right, let's move. Oh, go on, Brian.

[Brian Elliott]

The top decile private companies are larger than a huge portion of the public markets. And so the IPO market has gotten so onerous right now that private investors get access to all of the best deals in perpetuity. Companies like Stripe and Databricks. And so if you want to solve that, there needs to be a structural shift.

[Dave Blunden]

Yeah.

[Peter Diamandis]

All right, we'll move into our final. Our final segment here on health. And here's a piece. Apple Watch, hypertension alert receives FDA clearance. So listen, hypertension is a silent killer. 1.5 billion adults, 30 to 45% of the population, 60%, if you're over 60, is affected by hypertension. It's a systolic of one hundred and thirty or greater and a diastolic of greater than 80. And the challenge is that 46% of people with hypertension goes undiagnosed and only 21% is controlled. So if you can in fact get it handled by your Apple Watch, give you a heads up, but this is the beginning of the basically, wearables, insideables becoming part of our daily life. So I'm wearing a continuous glucose monitor. I've got my OURA ring, my Apple Watch, and I'm dribbling data actually into my AI, my Zori AI that I Have at fountain. And all of that data allows me to ask critical questions about my health. Has my deep sleep varied or my CGM levels varied with any particular medicine I'm taking or any particular supplement I'm taking? So it becomes really incredibly powerful. But what I really find exciting in this space is this announcement from Demis. DeepMind CEO says AI could shorten drug discovery to months. So Imad, you've been thinking about this a lot, the impact of AI on drug discovery and on health. What are your thoughts here?

[Imad Mustaq]

Yeah, I mean healthcare had to assume this ergonicity thing like we're all the same, we're all statistics. Everyone gets 500 milligrams of paracetamol for example. You know, the whole ASD thing. Actually paracetamol can impact you a bit more if you have a cytochrome P450 abnormality which causes metabolism. But how do you know that unless you've done tests like Fountain life? Right?

[Peter Diamandis]

Yeah.

[Imad Mustaq]

There's two parts to this. One is the ability to take all that data and, and think about everything from first principles, how all your systems interact. Then there are things like isomorphic labs which demis leads one of the spin outs there, the whole drug discovery thing. We can understand how compounds affect every part of our system and then that can accelerate these elements as long as they don't again get caught up by FDA and other red tape, that's unnecessary. Similarly, even as we do the trials right now, we just take down such little data. We can ask people how they feel and get massively rich data that comes in that allows us to extrapolate because data is data, knowledge is knowledge and we know how to compress and analyze that. I think you will find brand new drugs like again the first AI designed drug from isomorphic and clinical trials and we're seeing that elsewhere. But even repurposing of existing drugs I think will have a massive impact because again you have all this anecdote data that's out there, we have a whole bunch of compounds and we'll finally be able to analyze the masses of papers and trials properly to actually solve things. That's super exciting.

[Peter Diamandis]

Here's some of the numbers. So the first AI design drug comes from a friend, Alex Zavorankov. My bold venture capital fund is investor in silicone medicine. Just for full disclosure, but they've designed a drug for idiopathic pulmonary fibrosis that's in human trials right now. And then there's a drug called DSP1181. I love the names of these drugs. And it's for obsessive compulsive disease. And in particular it went from design to human trials in 12 months. Normally it takes four to five years. Here are some additional numbers. 150 small molecule drugs were discovered via AI first in 2025 alone. And at least 21 drugs have completed three phase one successfully with a success rate of 80 to 90%, which is stunning. We've talked about this imad that health and education are going to be two of the biggest areas fundamentally disrupted by AI and it really uplifts humanity.

[Imad Mustaq]

Yeah, I think it's just super exciting and I think what will be really interesting is I reckon in the next five years you might actually have part of the FDA process, what is the in silico, as it were, predictions of these drug trials and other things like that. And again, every part of that process, I think we can just shrink down and we can cure so many diseases as well as improve our own.

[Peter Diamandis]

Dave, closing thoughts for today.

[Dave Blunden]

I don't know how we're going to keep up. There's just so much every single week. It's funny, we, we were just riffing, what, for an hour, hour and a half? I don't know, whatever it was. But we had a whole nother agenda. We were going to talk about today too. We're going to have to reschedule that. But hey, this is the way it's going to be for the rest of our lives or at least for the next five years. The pace of acceleration is just crazy and you got to be in a full sprint mode at least for this time period. I think, Brian, it was great that you could join us today because your insight on now's the best time. There will never be a better time. There never has been a better time.

[Peter Diamandis]

Maybe tomorrow.

[Dave Blunden]

The fact that we pulled the. Well, the windows come and the windows go. So it's great to have your insights today.

[Peter Diamandis]

Yeah, yeah. Good to be here. And Brian, just thank you for the support you're giving this pod. Pleasure to have you and excited for those of our listener subscribers who reached out to Blitzy. Super cool. Yeah. And imod excited we're going to have you back on the pod in about a month when you come out to XPRIZE Visioneering. We're going to do a live WTF episode at XPRIZE Visioneering, which will be a lot of fun. And you and I will be talking a lot before we get to Saudi Arabia right after Visioneering. Anything you want to tell us about intelligent Internet right now?

[Imad Mustaq]

Yeah. Now release the new book on the new economy, thelasteconomy.com and we'll be releasing brand new math on how to think about the economy as we move forward when humans aren't the marginal innovator. It's a crazy time and we all got to think about this really carefully.

[Peter Diamandis]

It really is rewriting fundamental economic theory, period. Yeah, Brian, we stole you away from some meetings. What's your lineup for the rest of the day? You're just building furiously or engaging with customers?

[Brian Elliott]

Yeah, I'm going to hang out with customers. I like to hang out with the west coast clients between 6pm and 9pm because it's still work time there.

[Peter Diamandis]

Tom. Amazing. All right, everybody, thank you for another great episode of WTF. Please check out the [e-mail] WTF join us as a subscriber. Tell your friends about what we do. Our mission is to share sort of this extraordinary acceleration that we're feeling with you. Educate you along the way. Have fun, but get you ready for the new economy that Iman is writing about. Get you ready for the extraordinary future coming our way. Hope you'll trade an hour on the Crisis News Network for an hour with us instead. Everybody, have an amazing day and night and week. See you soon. Every week, my team and I study the top 10 technology metatrends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics and AGI and quantum computing to transport energy, longevity, and more. There's no fluff, only the most important stuff that matters that impacts our lives, our companies, and our careers. If you want me to share these metatrends with you, I write a newsletter twice a week, sending it out as a short 2 minute read via email. And if you want to discover the most important meta trends ten years before anyone else, this report's for you. Readers include founders and CEOs from the world's most most disruptive companies and entrepreneurs building the world's most disruptive tech. It's not for you if you don't want to be informed about what's coming, why it matters, and how you can benefit from it. To subscribe for free, go to dashmandis.com metatrends to gain access to the trends 10 years before anyone else. All right, now back to this episode.

[Imad Mustaq]

Mike and Alyssa are always trying to outdo each other. When Alyssa got a small water bottle, Mike showed up with a 4 liter jug. When Mike started gardening, Alyssa started beekeeping.

[Peter Diamandis]

Oh, come on.

[Imad Mustaq]

They called a truce for their holiday and used Expedia trip planner to collaborate.

[Dave Blunden]

On all the details of their trip.

[Imad Mustaq]

Once there, Mike still did more laps around the pool.

[Dave Blunden]

Whatever. You were made to outdo your holidays.

[Imad Mustaq]

We were made to help organize the competition. Expedia made to travel.